Diagnostic Algorithm of Multidetector Computed Tomography (MDCT) for Healthy Lungs to Detect Variations of Morphologic Index

U-Il Jong; Gyong-So Choe; Myong-Won Kim; Chang-Il Cho

Abstract

Introduction: Diagnostic algorithm of Multidetector Computed Tomography (MDCT) was established to make qualitative diagnosis with four types of shadows-increased Lung Attenuation, Decreased Lung Attenuation, Linear Pattern, Nodular Pattern and the nodular pattern is also used for qualitative assessment by being further classified as round, lobulated, polygonal, tentacular, spiculated, ragged and irregular pattern. Method: To establish the new diagnostic algorithm using MDCT result indicators, we selected morphologic indices to used CAD in healthy lungs for prediction of biopsy in lung diseases and identify their variations of bilateral lungs at each vertebral level among the 40 male and female volunteers respectively. Result: morphologic indices of healthy lungs at the level of vertebrae thoracales from No. 1 to 8, the significant deviation was observed in the area-round ratio, aspect ratio, equivdiameter, solidity, and second moment at the level of vertebrae thoracales from No. 4 to 8, though not observed from No. 1 to 3. Conclusion: Significant differences were observed in morphologic indices between bilateral lungs at slice level. Our own designed morphologic indices (such as area-round ratio, aspect ratio, solidity and second moment of human lung) may be reliable parameters in the establishment of CAD system and pathologic diagnosis for lung disease.

Abstract

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